Texture classification apparatus employing coarsensess and directivity of patterns
First Claim
1. An apparatus for classifying a textured image containing a plurality of pixels each of which is represented by a gray level value, which comprises:
- quantization means for obtaining a quantized image from the textured image, the quantized image containing a plurality of pixels each of which is represented by one of N quantized values, N being a positive integer;
means for scanning the quantized image along M scanning directions, M being a positive integer, to thereby provide M scanned images;
means for providing a set of runlengths by counting runlengths of pixels having a same quantized value, for each of the M scanned images and each of the N quantized values, to thereby provide M×
N sets of runlengths;
means for providing M×
N mean runlengths by averaging each set of runlengths;
means for forming an M×
N matrix whose elements are the mean runlengths;
means for determining a coarseness of the textured image by using the matrix;
means for determining a directivity of the textured image by using the matrix; and
means for classifying the textured image according to the coarseness and the directivity,wherein an element of the M×
N matrix is denoted as Lji, i being a positive integer ranging from 1 to M which designates each of the M scanning directions and j being a positive integer ranging from 1 to N which represents each of the N quantized values and the coarseness is determined as;
##EQU3## K being an integer representing the number of zero elements within the M×
N matrix.
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Abstract
An apparatus for classifying a textured image based on pattern coarseness and directivity comprises: a quantizer for obtaining a quantized image from the textured image, the quantized image containing a plurality of pixels each of which is represented by one of N quantized values, N being a positive integer; a scanning block for scanning the quantized image along M scanning directions, M being a positive integer, to thereby provide M scanned images; a grey level mean runlengths configuration block for providing a set of runlengths by counting runlengths of pixels having a same quantized value, for each of the M scanned images and each of the N quantized values, to thereby provide M x N sets of runlengths, providing M×N mean runlengths by averaging each set of runlengths, and forming an M×N matrix whose elements are the mean runlengths; pattern coarseness decision block for determining a coarseness of the textured image by using the matrix; pattern directivity decision block for determining a directivity of the textured image by using the matrix; and texture classification block for classifying the textured image according to the coarseness and the directivity.
49 Citations
15 Claims
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1. An apparatus for classifying a textured image containing a plurality of pixels each of which is represented by a gray level value, which comprises:
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quantization means for obtaining a quantized image from the textured image, the quantized image containing a plurality of pixels each of which is represented by one of N quantized values, N being a positive integer; means for scanning the quantized image along M scanning directions, M being a positive integer, to thereby provide M scanned images; means for providing a set of runlengths by counting runlengths of pixels having a same quantized value, for each of the M scanned images and each of the N quantized values, to thereby provide M×
N sets of runlengths;means for providing M×
N mean runlengths by averaging each set of runlengths;means for forming an M×
N matrix whose elements are the mean runlengths;means for determining a coarseness of the textured image by using the matrix; means for determining a directivity of the textured image by using the matrix; and means for classifying the textured image according to the coarseness and the directivity, wherein an element of the M×
N matrix is denoted as Lji, i being a positive integer ranging from 1 to M which designates each of the M scanning directions and j being a positive integer ranging from 1 to N which represents each of the N quantized values and the coarseness is determined as;
##EQU3## K being an integer representing the number of zero elements within the M×
N matrix. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10)
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11. An apparatus for classifying a textured image containing a plurality of pixels, each pixel being represented by a grey level value, which comprises:
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quantization means for obtaining a quantized image by quantizing the textured image based on the distribution characteristic of the pixels in the textured image, wherein the quantized image contains a plurality of pixels represented by one of N quantized values whose quantization intervals have widths adaptively determined based on the distribution characteristic of the pixels in the textured image, N being a positive integer; means for scanning the quantized image along M scanning directions, M being a positive integer, to thereby provide M scanned images; means for providing a set of runlengths by counting runlengths of pixels having a same quantized value, for each of the M scanned images and each of the N quantized values, to thereby provide M×
N sets of runlengths;means for providing M×
N mean runlengths by averaging each set of runlengths;means for forming an M×
N matrix whose elements are the M×
N mean runlengths;means for determining a coarseness of the textured image by using the matrix; means for determining a directivity of the textured image by using the matrix; and means for classifying the textured image based on the coarseness and the directivity, wherein an element of the M×
N matrix is denoted as Lij being a positive integer ranging from 1 to N which represents each of the N quantized values and i being a positive integer ranging from 1 to M which designates each of the M scanning directions and the coarseness is determined as;
##EQU5## K being an integer representing the number zero elements within the M×
N matrix. - View Dependent Claims (12, 13, 14, 15)
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Specification